A Case Study on Auction-Based Task Allocation Algorithms in Multi-Satellite Systems
Sean A. Phillips, Fernando Almeida Parra · AIAA Scitech 2021 Forum · 2021
View Video Presentation: https://doi.org/10.2514/6.2021-0185.vid In this paper, we consider the case of multiple satellites connected over a network that want to distribute Earth observation tasks across the network. There are numerous ways to distribute tasks in a decentralized manner across a network. We compare and contrast a class of algorithms known as auction-based task allocation algorithms for the multiple satellite scenario. Specifically, the three auction-based task allocation algorithms studied in this paper are: parallel single-item auctions (PSI), sequential single-item auctions (SSI), and the consensus-based bundle algorithm (CBBA). Our goal is to assign observation tasks to satellites in a way that minimizes the incidence angles and observation times of each task, as well as maximizes the total number of targets observed. The quality of the assignments generated by each algorithm, along with their resulting computation and communication costs, are compared within a simulation environment.